Improved Haptic Linear Lines for Better Movement Accuracy in Upper Limb Rehabilitation

Force feedback has proven to be beneficial in the domain of robot-assisted rehabilitation. According to the patients' personal needs, the generated forces may either be used to assist, support, or oppose their movements. In our current research project, we focus onto the upper limb training for MS (multiple sclerosis) and CVA (cerebrovascular accident) patients, in which a basic building block to implement many rehabilitation exercises was found. This building block is a haptic linear path: a second-order continuous path, defined by a list of points in space. Earlier, different attempts have been investigated to realize haptic linear paths. In order to have a good training quality, it is important that the haptic simulation is continuous up to the second derivative while the patient is enforced to follow the path tightly, even when low or no guiding forces are provided. In this paper, we describe our best solution to these haptic linear paths, discuss the weaknesses found in practice, and propose and validate an improvement. 1. Introduction Force feedback applications show their benefits when they are applied in a robot-assisted rehabilitation program [1, 2]. In such a setup, the training can be more finely tailored to the abilities and needs of the patient. At the same time, less assistance of the therapist may be required, allowing at the longer term to abolish the “one therapist for one patient” requirement. The ultimate goal should be to allow patients to perform their training independently without active assistance of the therapist, or even to use the force feedback enabled setup at home while being remotely monitored [3, 4]. It may sound evident that this opens possibilities for cost reduction or an increased training intensity, where the latter at its turn provides better training results [5]. Additionally, several studies suggest that using games in a therapy may improve the patient’s motivation [6]. Not necessarily using force feedback, but surely by bringing the computer to the revalidation setup and exploiting the “fun”-factor, this improvement in motivation may be achieved. Our research lab participated in a pilot study focussing on the training of the upper limbs in Multiple Sclerosis (MS) (MS is an autoimmune disease of the central nervous system, resulting in an increasing loss of force and coordination) patients [7]. As the results were promising, the project was prolonged and the focus was broadened to both MS and CVA (CVA: cerebrovascular accident or stroke is the loss of brain function(s) due to disturbance in the blood supply to the